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Researchers at Baylor College of Medicine have developed a powerful new data analysis method named COOKIE-Pro (Covalent Occupancy Kinetic Enrichment via Proteomics) that provides a comprehensive, unbiased view of how a class of drugs, called covalent inhibitors, interacts with proteins throughout the cell.

This innovative technique, in Nature Communications, promises to accelerate the design of more effective and safer therapeutics by precisely measuring both the binding strength and reaction speed of these drugs against thousands of potential targets simultaneously.

"Covalent inhibitors, which include well-known drugs like aspirin and the cancer therapeutic ibrutinib, are highly effective because they form a strong, permanent bond with their target protein," said corresponding author of the work Dr. Jin Wang, director of the Center for NextGen Therapeutics and Michael E. DeBakey, M.D. Endowed Professor in Pharmacology at Baylor. "However, this strength can be a double-edged sword; these drugs can also bind to unintended off-target proteins, potentially leading to unwanted side effects."

Optimizing these drugs requires a delicate balance between how strongly they are attracted to a target (affinity) and how quickly they form the permanent bond (reactivity). Until now, methods to measure these two crucial parameters across the entire cellular protein landscape, or proteome, have been limited, slowing down drug development.

"The challenge was getting a clear, complete picture," said Hanfeng Lin, the study's first author and a graduate student in the Wang lab. "We knew we needed to measure both affinity and reactivity, but doing it for one protein takes time, let alone thousands. COOKIE-Pro gives us a comprehensive map in which we can see for the first time, not just if a drug binds off-target, but how well and how fast, which is critical information for drug designers."

COOKIE-Pro overcomes this challenge with a two-step process. First, researchers break down cells in a liquid solution and then add the covalent drug, allowing it to bind to its targets. Next, they introduce a specially designed "chaser" probe that latches onto any protein-binding sites left unoccupied by the drug. By using mass spectrometry to measure how much of the chaser probe binds, they can precisely deduce how "occupied" each protein was by the drug. This allows them to calculate both the binding affinity and the inactivation rate for thousands of proteins at once.

The team validated the method using two well-studied drugs, spebrutinib and ibrutinib. The findings not only accurately reproduced previous results but also uncovered new insights. For instance, they discovered that spebrutinib, a highly selective enzymatic inhibitor, is surprisingly more than 10 times more potent against an off-target protein, TEC kinase, than its intended target, BTK. For the less-selective drug ibrutinib, COOKIE-Pro successfully identified its known off-targets and generated profiles that aligned with previously published values, confirming the method's accuracy.

"The ultimate goal is rational drug design," said Wang, professor of biochemistry and molecular pharmacology and of molecular and cellular biology at Baylor. He is also a member of Baylor's Dan L Duncan Comprehensive Cancer Center.

"A drug might appear potent because it binds quickly, but if that is simply because it has a 'hot' reactive group, it might cause side effects by binding everywhere. COOKIE-Pro allows us to separate that intrinsic reactivity from true binding affinity. We can now help chemists prioritize compounds that are potent because they bind specifically to the right target, not just because they are broadly reactive. This is a crucial step toward creating the next generation of highly selective and safer covalent medicines."

Furthermore, the team demonstrated the platform's power for large-scale drug screening by developing a streamlined two-point COOKIE-Pro strategy. Applying this high-throughput approach to a library of 16 covalent inhibitor fragments, they generated thousands of profiles, proving the method's capability to quickly and efficiently guide the earliest stages of drug discovery.

Co-authors Bin Yang, Lang Ding, Matthew V. Holt, Sung Yun Jung and Bing Zhang are all affiliated with Baylor College of Medicine. Co-author Meng C. Wang is affiliated with Howard Hughes Medical Institute and co-author Yen-Yu Yang is with Thermo Fisher Scientific.